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Effective Multi-Model Motion Tracking using Action Models

Computer Science Department Carnegie Mellon University Pittsburgh, Pennsylvania 15213, USA, guyang{at}cs.cmu.edu

Manuela Veloso

Computer Science Department Carnegie Mellon University Pittsburgh, Pennsylvania 15213, USA, velosa{at}cs.cmu.edu

We consider tasks where robots act on the target that is visually tracked, such as kicking a ball or pushing an object. We introduce a principled approach to incorporate models of the robot-object interaction into the tracking algorithm to effectively improve the performance of the tracker. We first present the integration of a single robot behavioral model with multiple actions into our dynamic Bayesian probabilistic tracking algorithm. We then extend to multiple motion tracking models corresponding to known multi-robot coordination plans or from multi-robot communication. We evaluate our resulting informed-tracking approach empirically in simulation and using a setup Segway robot soccer task. The input of the multiple single and multi-robot behavioral models allows a robot to visually track mobile targets with dynamic trajectories more effectively.

Key Words: multi-model • motion tracking • human-robot-team • action models

The International Journal of Robotics Research, Vol. 28, No. 1, 3-19 (2009)
DOI: 10.1177/0278364908097587


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